Arvind K. Saibaba

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Peter K. KitanidisProfessor, Stanford UniversityPatvirtintas el. paštas stanford.edu
Misha KilmerTufts UniversityPatvirtintas el. paštas tufts.edu
Alen AlexanderianNorth Carolina State UniversityPatvirtintas el. paštas ncsu.edu
Julianne ChungEmory UniversityPatvirtintas el. paštas emory.edu
Scot M. MillerJohns Hopkins UniversityPatvirtintas el. paštas jhu.edu
Ilse C. F. IpsenProfessor of Mathematics, North Carolina State UniversityPatvirtintas el. paštas ncsu.edu
Mirjeta PashaNSF Postdoctoral Associate at Massachusetts Institute of TechnologyPatvirtintas el. paštas mit.edu
Tania BakhosAmazonPatvirtintas el. paštas amazon.com
Eric de SturlerProfessor, Department of Mathematics, Virginia TechPatvirtintas el. paštas vt.edu
Eric MillerTufts UniversityPatvirtintas el. paštas tufts.edu
Jonghyun "Harry" LeeUniversity of Hawaii at ManoaPatvirtintas el. paštas hawaii.edu
D. Andrew BrownAssociate Professor, School of Mathematical and Statistical Sciences, Clemson UniversityPatvirtintas el. paštas clemson.edu
Eric DarveStanfordPatvirtintas el. paštas stanford.edu
Sivaram AmbikasaranIIT MadrasPatvirtintas el. paštas iitm.ac.in
Bart van Bloemen WaandersSandia National LaboratoriesPatvirtintas el. paštas sandia.gov
Eric HallmanApplied Researcher, eBayPatvirtintas el. paštas ncsu.edu
Shuchin AeronAssociate Professor, ECE, Tufts UniversityPatvirtintas el. paštas ece.tufts.edu
Agnieszka MiedlarAssociate Professor, Virginia TechPatvirtintas el. paštas vt.edu
Ahmed AttiaComputational Mathematician, Argonne National Laboratory, USAPatvirtintas el. paštas mcs.anl.gov
DANIEL B. SZYLDDepartment of Mathematics, Temple University, PhiladelphiaPatvirtintas el. paštas temple.edu

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Arvind K. Saibaba

Associate Professor, North Carolina State University

Patvirtintas el. paštas ncsu.edu - Pagrindinis puslapis

Inverse problems Numerical Linear Algebra Uncertainty Quantification


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Randomized algorithms for low-rank tensor decompositions in the Tucker format R Minster, AK Saibaba, ME Kilmer SIAM journal on mathematics of data science 2 (1), 189-215, 2020	83	2020
Randomized matrix-free trace and log-determinant estimators AK Saibaba, A Alexanderian, ICF Ipsen Numerische Mathematik 137 (2), 353-395, 2017	83	2017
A randomized tensor singular value decomposition based on the t‐product J Zhang, AK Saibaba, ME Kilmer, S Aeron Numerical Linear Algebra with Applications 25 (5), e2179, 2018	80	2018
Randomized algorithms for generalized Hermitian eigenvalue problems with application to computing Karhunen–Loève expansion AK Saibaba, J Lee, PK Kitanidis Numerical Linear Algebra with Applications 23 (2), 314-339, 2016	67	2016
Goal-oriented optimal design of experiments for large-scale Bayesian linear inverse problems A Attia, A Alexanderian, AK Saibaba Inverse Problems 34 (9), 095009, 2018	65	2018
Efficient methods for large-scale linear inversion using a geostatistical approach AK Saibaba, PK Kitanidis Water Resources Research 48 (5), W05522, 2012	57	2012
Efficient D-optimal design of experiments for infinite-dimensional Bayesian linear inverse problems A Alexanderian, AK Saibaba SIAM Journal on Scientific Computing 40 (5), A2956-A2985, 2018	55	2018
A flexible Krylov solver for shifted systems with application to oscillatory hydraulic tomography AK Saibaba, T Bakhos, PK Kitanidis SIAM Journal on Scientific Computing 35 (6), A3001-A3023, 2013	53	2013
The discrete empirical interpolation method: Canonical structure and formulation in weighted inner product spaces Z Drmac, AK Saibaba SIAM Journal on Matrix Analysis and Applications 39 (3), 1152-1180, 2018	50	2018
Randomized subspace iteration: Analysis of canonical angles and unitarily invariant norms AK Saibaba SIAM Journal on Matrix Analysis and Applications 40 (1), 23-48, 2019	49	2019
Fast computation of uncertainty quantification measures in the geostatistical approach to solve inverse problems AK Saibaba, PK Kitanidis Advances in water resources 82, 124-138, 2015	48	2015
Application of hierarchical matrices to linear inverse problems in geostatistics AK Saibaba, S Ambikasaran, JY Li, PK Kitanidis, EF Darve Oil & Gas Science and Technology–Revue d’IFP Energies nouvelles 67 (5), 857-875, 2012	45	2012
Generalized hybrid iterative methods for large-scale Bayesian inverse problems J Chung, AK Saibaba SIAM Journal on Scientific Computing 39 (5), S24-S46, 2017	43	2017
Efficient generalized Golub–Kahan based methods for dynamic inverse problems J Chung, AK Saibaba, M Brown, E Westman Inverse Problems 34 (2), 024005, 2018	40	2018
HOID: higher order interpolatory decomposition for tensors based on Tucker representation AK Saibaba SIAM Journal on Matrix Analysis and Applications 37 (3), 1223-1249, 2016	35	2016
Geostatistical inverse modeling with very large datasets: an example from the Orbiting Carbon Observatory 2 (OCO-2) satellite SM Miller, AK Saibaba, ME Trudeau, ME Mountain, AE Andrews Geoscientific Model Development 13 (3), 1771-1785, 2020	32	2020
Multipreconditioned GMRES for shifted systems T Bakhos, PK Kitanidis, S Ladenheim, AK Saibaba, DB Szyld SIAM Journal on Scientific Computing 39 (5), S222-S247, 2017	28	2017
Randomized algorithms for rounding in the tensor-train format H Al Daas, G Ballard, P Cazeaux, E Hallman, A Międlar, M Pasha, ... SIAM Journal on Scientific Computing 45 (1), A74-A95, 2023	27	2023
Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis AK Saibaba, J Hart, B van Bloemen Waanders Numerical linear algebra with applications 28 (4), e2364, 2021	24	2021
Low-rank independence samplers in hierarchical Bayesian inverse problems DA Brown, A Saibaba, S Vallélian SIAM/ASA Journal on Uncertainty Quantification 6 (3), 1076-1100, 2018	23*	2018

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